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Stochastic optical reconstruction microscopy (STORM) and related methods achieves sub-diffraction-limit image resolution through sequential activation and localization of individual fluorophores. The analysis of image data from these methods has typically been confined to the sparse activation regime where the density of activated fluorophores is sufficiently low such that there is minimal overlap between the images of adjacent emitters. Recently several methods have been reported for analyzing higher density data, allowing partial overlap between adjacent emitters.

Bayesian analysis of blinking and bleaching, or 3B microscopy, is a method which analyses data in which many overlapping fluorophores undergo bleaching and blinking events, giving the structure at enhanced resolution.

SimpleITK provides a simplified interface to ITK in a variety of languages. A user can either download pre-built binaries, if they are available for the desired platform and language, or SimpleITK can be built from the source code. Currently, Python binaries are available on Microsoft Windows, GNU Linux and Mac OS X. C# and Java binaries are available for Windows. We are also working towards supporting R packaging.

The Cython language is a superset of the Python language that additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code.

ZEN and APEER – Open Ecosystem for integrated Machine-Learning Workflows

Open ecosystem for integrated machine-learning workflows to train and use machine-learning models for image processing and image analysis inside the ZEN software or on the APEER cloud-based platform

R wrapper around the OMERO Java Gateway, to enable access to OMERO via R using rJava

Bisque (Bio-Image Semantic Query User Environment) : Store, visualize, organize and analyze images in the cloud. It also allow to run workflows using a set of deployed tools, such as CellProfiler, RootTipMultin Nuclear Tracker, Microtubule tracker etc...

Bisque was developed for the exchange and exploration of biological images.

OpenImadis stands for Open Image Discovery: A platform for Image Life Cycle Management. It was previously called CID iManage (for Curie Image Database).

No image data conversions, no duplication.

- Uploads data to a secure server in the original format

ScientiFig is a free tool to help you create, format or reformat scientific figures. It comes either as a stand alonesoftware, either as a Fiji/IJ plugin.

This notebook uses the rOMERO-gateway and EBImage to process an Image associated to the paper 'Timing of gene expression in a cell-fate decision system'.

This one example workflow from the Cell Profiler(CP)  Examples . CP is commonly used to count cells or other objects as well as percent-positives, by measuring the per-cell staining intensity. This pipeline shows how to do both of these tasks, and demonstrates how various modules may be used to accomplish the same result. 

This is a Jupyter notebook demonstrating the run of a code from IDR data sets by loading a CellProfiler Pipeline 

The example here is applied on real data set, but does not correspond to a biological question. It aims to demonstrate how to create a jupyter notebook to process online plates hosted in the IDR.

It reads the plate images from the IDR.

This workflow can be ran with data from 3D-SIM showing the centrosomes in order to compare the distribution of diameters of rings (or toroids) of different proteins from the centrioles or the peri centriolar material. It aims to reproduce the results of the Nature Cell Biology Paper Subdiffraction imaging of centrosomes reveals higher-order organizational features of pericentriolar material  from the same data set but with a different analysis method.

The Image.sc forum focuses on software-oriented aspects of scientific imaging, particularly (but not limited to) image analysis, processing, acquisition, storage, and management of digital scientific images. The primary objective is to foster independent learning for everyone in the community.

Python/C++ port of the ImageJ extension TurboReg/StackReg written by Philippe Thevenaz/EPFL.

A python extension for the automatic alignment of a source image or a stack (movie) to a target image/reference frame.

A collection of components for super resolution image data:

• Detect Molecules
• Reconstruct Image
• Results table
• Drift correction
• Chromatic correction